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Journal article

Humanization of antibodies using a machine learning approach on large-scale repertoire data

Abstract:

Motivation: Monoclonal antibody therapeutics are often produced from non-human sources (typically murine), and can therefore generate immunogenic responses in humans. Humanization procedures aim to produce antibody therapeutics that do not elicit an immune response and are safe for human use, without impacting efficacy. Humanization is normally carried out in a largely trial-and-error experimental process. We have built machine learning classifiers that can discriminate be...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/bioinformatics/btab434

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Kellogg College
Role:
Author
More by this author
Oxford college:
Kellogg College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Kellogg College
Role:
Author
More by this author
Institution:
University of Oxford
Department:
STATISTICS
Sub department:
Statistics
Oxford college:
Kellogg College
Role:
Author
ORCID:
0000-0003-1388-2252
Publisher:
Oxford University Press Publisher's website
Journal:
Bioinformatics Journal website
Volume:
37
Issue:
22
Pages:
4041–4047
Publication date:
2021-06-10
Acceptance date:
2021-06-07
DOI:
EISSN:
1460-2059
ISSN:
1367-4803
Language:
English
Keywords:
Pubs id:
1181328
Local pid:
pubs:1181328
Deposit date:
2021-06-10

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